InetSoft's Enterprise Data Management Software: Data Mashup Plus Dashboard Reporting
Looking for enterprise data management software? InetSoft offers Web-based BI software that includes a powerful and flexible data mashup tool with direct access to disparate data sources of almost any type. Below are articles related to InetSoft's software.
Data Provides Insight into Forecasting - As far as other companies, yes, I do think that all of that historical data provides insight into forecasting. We have used the information that we are pulling in for planning and not only for your typical annual budgets or your cash flow forecasting, but we have used it to really look at the products that we are offering and determine what the best strategy will be for the upcoming year. So for instance, we might run a seasonal promotion in the summer around a mango salsa, or a burrito, because we think it’s springy, and people are going to gravitate towards it. But if that falls flat, then that information is saved in the data that says well may be we’ll push a different promotion around that ingredient in the summer next year. So we are able to use that information not just for our budgeting purposes, but for really product innovation, limited time only specials, and stuff like that. That’s really essential for us in order to maximize performance. For us in the coming year, we are going to put a lot of effort into the customer, and gathering as much information as we can...
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Click this screenshot to view a two-minute demo and get an overview of what InetSoft’s BI dashboard reporting software, Style Intelligence, can do and how easy it is to use. |
Data Scientists and Domain Experts - When we talk about the current machine learning adoption trends, are we expecting data scientists to be domain experts, to be business domain experts? Is that a realistic expectation? I think that there's this myth of the 23-year old data scientist who knows about math, knows about computers and knows about business. I think there's plenty of really smart, super sharp people out there, young people out there who may really know math and statistics and really may know their computer hacking skills extremely well, but that substantive expertise can take years to develop. I think there's a little - if we are lumping business expertise into the data scientist definition, then I think that takes some time to cultivate for sure. Some problems that we see with data scientists and managing data scientists is sometimes if this is a new function in an organization, management might not really understand how they need to work. One classic pitfall is getting bogged down with algorithms. Spending all your time picking the best algorithm or trying to tune algorithms instead of just focusing on solving the business problem, instead of focusing on the fastest way to solve the business problem. There can be all kinds of issues between data science and IT, who owns the data, who owns the tools, who owns the hardware that can cause conflict...
Data Services Platform - One of the common ways how data services have been leveraged to deliver this agile business intelligence to this process is by providing a data services platform that has first of all access to disparate data resources, and we will talk not only about some of the more sophisticated customers we have, how they have enhanced the user experience beyond just sort of the core enterprise applications to bring in Web data and some of the other customer feedback information to be able to relate that back to product catalogs, etc. So we obviously can take inputs into this from several computer-telephony Integration products like the Avaya, the Genesys systems so you have that in call center integration....
Data Services Platform Presents Different Views - But in every case, these examples of data mashups of transactional data are dealing with the customers. They are making decisions. Let me go back to the telco example. They may be answering the billing questions. Then they might be answering a technical support issue and then going into an up-sell, cross-sell mode to offer the customer something more. Depending on the context, the data services platform is able to present different views to the front-end system. So the actual claim, the order the transaction might actually continue to flow through transactional systems meaning they work through SOA type middleware, but in presenting the context behind making such a decision, the customer agent or operational person needs a lot of information. Sometimes, it's not even an agent. It's a self-service customer portal where the customer comes in and wants to check the status of their orders, check out what are the products that are available. The intelligence of the data services platform in combining multiple external and internal data sources and presenting them at the right moment is very valuable in actually offloading back-office work from the agent to self service portals, but also in making the agent very productive. So this is a very typical use case, and we have implemented multiple systems where data virtualization is used in the support of call centers, customer self-service portals, agent portals, single customer views, etc...
Data Sharing and Analysis Between Enterprise Systems - This brings me to the next point. Why is there so much disconnection between enterprise systems from a data sharing and analysis standpoint? I mean given these information silos, is there a way for finance to leverage its investments more effectively? Well, without a doubt, the CFO has the opportunity based upon the knowledge that, if you didn’t have it before today’s webinar, then you hopefully walk away from it with. The ability to integrate and synchronize data to have what you might call one version of the truth is absolutely possible. Now there are challenges and certainly some of these information silos come from the disparate histories or roadmaps of technology acquisition, whether it was through companies being acquired or merged or if you were served by self-sufficient IT. There are a variety of reasons why the data may not be internally integrated, but it is entirely possible to do so, and there are good reasons why this makes good business sense. You can see here in the slide. You can see that I am showing you here in dark blue the users of a well-integrated mobile BI infrastructure, which implies, if you will, this data harmonization and that there are on-users, those who do not actually have this capability at all...
Data Supply Chain - Its Definition and How to Use It - We have all heard of supply chains in the context of manufacturing, for example, but what exactly is a data supply chain? The data supply chain is a lifecycle for data that basically propagates and procures data on behalf of the corporation. So if you look at data as being bigger than the platform, when we truly talk about enterprise data, we are talking beyond the data warehouse. We are talking about enterprise data as an asset on behalf of the corporation. What the supply chain does is it basically looks at data, the inputs and outputs of data across the company, across systems, across platforms, across organizations and really manages it as an asset. We apply the same principles of a normal manufacturing supply chain to data, and the advantage of that is that executives speak that language. As we discuss supply chains, we are really establishing a common vocabulary around data that executives can understand...
Data Tables - Tables offer a number of special properties that allow you to access the data values from script, and to add visual style to rows, columns, and individual cells. The following sections explain how to use these properties. There are two key properties for accessing the values in a table, table and data. • table – A two-dimensional array containing the table data as displayed. The array includes header rows as well as data rows. • data – A two dimensional array containing the raw table data (prior to grouping and summarization). It does not include header rows. Two sub-properties that are especially useful when looping through the rows or columns of tables are 'length' and 'size'. Note: A table that returns no data still displays the column header row. Therefore, table.length is 1 in the no-data case...
Data Transformation Tool for Dashboards - Looking for a good dashboard data transformation tool to prepare your data for interactive dashboards? InetSoft's pioneering dashboard reporting application enables real-time data transformation connected to live data sources to power great-looking web-based dashboards, all with an easy-to-use drag-and-drop designer and SQL editor. View a demo and try interactive examples...
Data Virtualization - You should consider best-of-breed platforms that enable agile data access. Make sure they cover a full range of data virtualization and data and information integration services that address both your needs to bring in structured and unstructured information across your Internet and across the Web. So longer term, you can re-architect your BI and data services environments to enable maximum agility according to the model that I laid out earlier in this Webinar. Move your best practices, move your internal practices for developing BI and data services away from the traditional waterfall style, a time consuming, a silo-friendly approach towards more of an agile approach that’s fast and flexible and collaborative and iterative...
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Click this screenshot to view a two-minute demo and get an overview of what InetSoft’s BI dashboard reporting software, Style Intelligence, can do and how easy it is to use. |
Data Visualization Benefits - The benefits of data visualization are endless. Business' can utilize a visualization in many different ways, and it creates another level of understanding for the user. Normally, raw data is a long tedious list of information. All of this can be really hard to decipher from especially with larger data sets. However, if a visualization is implemented all of a sudden the data becomes clear to the user. Humans learn more from visualizations than from reading and trying to understand large data sets. If a large data set is put into something like a pie chart then it's easy to tell what category has more or is doing better financially or whatever the topic may be...
Data Visualization Gallery - Click on an image to learn about the different dashboards. These industry specific executive dashboards allow you to get a feel for how easy it to use InetSoft's dashboard software. Capital Markets, Education Dashboard, Government Dashboard, Healthcare Dashboard, Insurance Dashboard, Manufacturing Dashboard, Midsize Enterprise Dashboard, Retail Banking Dashboard, Technology Dashboard...
Data Visualization Software and Dashboards for OLAP Databases - InetSoft's dashboard and data visualization software can access many of the popular OLAP databases such as Oracle Hyperion Essbase, Oracle OLAP, MS Analysis Server, and SAP NetWeaver BW. In addition to accessing a single OLAP server for advanced dashboarding and analytics, InetSoft's powerful data mashup engine allows for combining and manipulating data with other data types (see All Data Sources for others), saving on additional ETL efforts. With a small-footprint server, agile data access, and intuitive design tools, InetSoft's Style Intelligence delivers the IT-friendliest database reporting tools for user-friendly self-service business intelligence...
Data Visualization Software Download - Are you looking to download data visualization software? Since 1996 InetSoft has been making business software that is easy to deploy and easy to use. Build self-service oriented dashboards and visual analyses quickly. View a 3-minute demo and download a free version...
Data Warehouse BI Solution - InetSoft makes BI software that can mash up data from data warehouses and almost any other operational data source and deliver dashboard reporting for a unified view of corporate performance.InetSoft's unique data mashup capabilities also speed up data warehouse architecture update processes. It allows you to prototype data maniupulations before committing to new, official ETL definitions and transformations...
Data Warehouse BI Tool - Searching for an information management solution that doesn't rely on ETL processes or a data warehouse? Consider using InetSoft's Web-based data mashup business intelligence software. The data mashup engine allows you to combine disparate data sources in real-time for dashboard reporting...
Data Warehouse Reporting Tool - Looking for data warehouse reporting tools? Since 1996 InetSoft has been making dashboard reporting software that is easy to deploy and easy to use and connects to data warehouses and almost any other data source, operational databases, spreadsheets, cloud sources, etc, so you don't have to build new ETL processes. A powerful data transformation and mashup tool and a drag and drop dashboard and report designer allows for rapid creation of self-service-oriented views of data...
Data Warehouse Reports - With the self-service capabilities of Style Intelligence, you can use to create dashboards and reports on your data warehouse or analytics environment, and you can do this very fast, and you can do it with new set of users such as salesforces or people in the C level. nment where it makes sense. You have really the BI systems drive a different way of doing business in the marketplace. So what we hear is great response on the whole about usability, great response about implementation time because you can really do something up and running very fast. The next thing is we also hear a lot of things that a lot of customers need to now rethink their business strategies to take advantage of this new kind of analytic solution. They are not used to having all this information at their fingertips. So, there are also some changes in organizational models that are happening right now. There are some changes in BI competency centers and data governance because people w ant to have access to this kind of solution. This is something that IT departments have to cope with in the long run...
Data Warehouses as Refrigerator-sized Appliances - Normally you think of data warehouses as a single refrigerator-sized appliance, but you can connect them. They can be massively parallel together. Then you have distributed technologies. Hadoop is the most notable, but you also have NOSQL. When it comes to other business intelligence technology, it really depends on the way that you are using them. If you are using them to be more affordable for extreme scale problems, they can be tools in your Big Data toolkit. Things like Cassandra and HBase offer you different tradeoffs between consistency, availability and partition tolerance. That’s also another thing that we find in Big Data solutions is they tend to force you to make these kinds of tradeoffs because to be highly available typically you have to either give up consistency or tolerance to partitions. And so we see these tradeoffs being made so those kinds of databases like HBase or Cassandra that make those tradeoffs and are massively parallel tend to be used to handle extreme scale. Therefore they can be Big Data tools...